The present invention relates generally to a dialog performance improvement method, and more particularly, but not by way of limitation, to a system, method, and computer program product for improving dialog quality through self-learning from user feedback.
Many virtual agents, bots and full-fledged robots employ spoken dialog to try to provide enhanced human-machine interaction. The dialog service quality heavily depends on voice recognition, and a classification model. However, quality is often poor.
Some conventional techniques have considered dynamic user feedback in a guide that is presented to the user. The feedback presented in the guide enables the user to refine the classification model by adding or removing exemplars, creating, editing or deleting rules, or performing other such adjustments to the classification model. However, the conventional techniques require extensive user re-programming of the dialog system in order to improve the dialog performance.